Amazon Quick announces autonomous agents, multi-dataset analytics, and redesigned activity feed
Quick's new autonomous agents handle your busywork 24/7—stalled deals, compliance alerts, POs—while you focus on what actually matters.
View original announcement →Visual Summary
graph TD
A{{Amazon Quick}}:::announced
B([Autonomous Agents]):::feature
C([Multi-Dataset Analytics]):::feature
D([Activity Feed]):::feature
E(AWS Glue):::storage
F(Snowflake):::storage
G((Business User)):::external
H([Identity Propagation]):::feature
I((External Stakeholders)):::external
G ==>|"natural language"| A
A -->|"continuous tasks"| B
A -->|"cross-source queries"| C
A -->|"prioritized view"| D
C -->|"inherits metadata"| E
C -->|"queries data"| F
C -->|"enforces permissions"| H
B -.->|"learns from"| G
D -.->|"public sharing"| I
classDef announced fill:#ff9900,stroke:#ec7211,color:#fff,font-weight:bold
classDef compute fill:#e3f2fd,stroke:#1565c0,color:#1565c0
classDef storage fill:#e8f5e9,stroke:#2e7d32,color:#2e7d32
classDef feature fill:#fff3e0,stroke:#e65100,color:#e65100
classDef external fill:#f5f5f5,stroke:#616161,color:#616161
What's New
AWS has announced three major capability expansions for Amazon Quick, its AI work assistant: autonomous agents that execute recurring business workflows continuously in the background, multi-dataset analytics that enables natural language querying across heterogeneous data sources without manual data preparation, and a redesigned activity feed that consolidates communications and tasks into a single prioritized, conversational interface. These features collectively shift Quick from a reactive assistant to a proactive, always-on automation platform. Users can get started for free at aws.com/quick.
How It Works
- Autonomous Agents: Users describe tasks in plain language or select from a pre-configured agent library; each agent is assigned a granular autonomy level ranging from step-by-step human approval to broad goal-based self-directed execution, and operates continuously in the background without coding.
- Agent Learning Loop: Every correction, interaction, and outcome is fed back into the agent's model, progressively improving its accuracy and judgment over time, similar to an on-the-job learning colleague.
- Multi-Dataset Analytics: Quick accepts natural language queries and resolves them across multiple connected data sources—including Snowflake and relational databases—without requiring users to pre-join or transform datasets beforehand.
- Semantic Catalog Inheritance: Quick ingests semantic metadata and business context from existing data catalogs (AWS Glue, Databricks Unity Catalog, Collibra), allowing it to understand business terminology and relationships already defined by data teams.
- Identity Propagation for Security: Data access is governed by propagating the querying user's existing identity and permissions through to the underlying data sources, ensuring no privilege escalation occurs during cross-source queries.
- Redesigned Activity Feed: Email, Slack, calendar events, and task items are consolidated into a single feed; a feedback mechanism (thumbs up/down) trains the feed's prioritization model, and users can reply to messages or approve requests inline without switching applications.
- Public Website Sharing: Quick applications and dashboards can be published as public-facing websites, enabling collaboration and insight sharing with external stakeholders outside the organization.
Why It's Important
- Eliminates Repetitive Knowledge Work at Scale: Autonomous agents handle high-frequency, low-judgment tasks (deal follow-ups, PO processing, regulatory summarization) around the clock, directly recovering productive hours for knowledge workers without requiring engineering resources.
- Democratizes Cross-Source Analytics: By removing the need for SQL expertise, ETL pipelines, or manual dataset joins, multi-dataset analytics makes complex, multi-system business questions accessible to non-technical users in real time.
- Reduces Context-Switching Overhead: The unified activity feed addresses a well-documented productivity drain—triage across fragmented communication tools—by surfacing prioritized, actionable items in one place.
- Leverages Existing Data Governance Investments: Inheriting semantic intelligence from catalogs like AWS Glue and Collibra means organizations don't need to re-annotate or duplicate metadata, protecting prior investments and accelerating time-to-value.
- Maintains Security Posture: Identity propagation ensures that autonomous agents and cross-source queries respect existing row-level, column-level, and object-level permissions, which is critical for regulated industries.
- Extends Organizational Reach: Public website sharing allows Quick-generated insights and applications to reach customers, partners, and external stakeholders without requiring them to have a Quick account.
How It's Different
- Continuous vs. On-Demand Execution: Unlike most AI assistants that respond only when prompted, Quick's autonomous agents operate persistently in the background, completing work even when the user is unavailable or in meetings.
- Adjustable Autonomy Spectrum: Rather than a binary "auto-approve or manual" model, Quick offers a granular autonomy dial from fully supervised to fully autonomous, giving users fine-grained control over risk tolerance per task type.
- No-Code Agent Creation: Competing workflow automation tools (e.g., Zapier, Power Automate) typically require trigger-action configuration; Quick agents are created through natural language descriptions with no visual or code-based workflow design required.
- Catalog-Aware Semantic Querying: Unlike generic text-to-SQL tools, Quick inherits business context from enterprise data catalogs, meaning it understands domain-specific terminology and relationships without additional prompt engineering.
- Federated Query Without ETL: Rather than requiring data to be centralized or pre-joined into a warehouse, Quick queries data in place across Snowflake, relational databases, and other sources, reducing data movement and latency.
- Inline Action from the Feed: Most unified inbox tools (e.g., Superhuman, Slack) surface information but require navigation to source systems to act; Quick's activity feed allows replies, approvals, and task completions directly within the interface.
When to Prefer It
- Sales Operations Teams: When reps need stalled deals flagged, CRM notes auto-updated, and follow-up drafts prepared without manual review of every pipeline entry after a day of customer calls.
- Compliance and Legal Functions: When regulatory monitoring is required continuously—such as tracking legislative changes overnight and generating impact summaries before business hours—without dedicated analyst bandwidth.
- Finance and Procurement Teams: When purchase order volumes are high and routine approvals or processing steps can be delegated to an agent operating 24/7, freeing staff for strategic vendor negotiations.
- Data Analysts and Business Users Without SQL Skills: When business questions span multiple systems (e.g., CRM + data warehouse + operational database) and the user lacks the technical ability or time to write joins and transformations.
- Organizations with Mature Data Catalogs: When AWS Glue, Databricks Unity Catalog, or Collibra are already in use and the organization wants to leverage that semantic investment for natural language analytics without rebuilding metadata.
- Teams with High Communication Volume: When employees spend the first hour of each day triaging email and Slack rather than doing substantive work, and a prioritized, actionable feed would materially improve focus.
- External Collaboration Use Cases: When insights, dashboards, or Quick-built applications need to be shared with customers or partners who are outside the organization's identity perimeter.
Availability
- General Availability: All three features—autonomous agents, multi-dataset analytics, and the redesigned activity feed—were announced as generally available on June 17, 2026.
- Free Tier: Amazon Quick offers a free account tier; users can sign up and get started in minutes at aws.com/quick with no upfront commitment.
- Paid Tiers: Enterprise pricing is available separately; the product page references distinct individual and enterprise pricing tiers, though specific per-seat costs were not disclosed in the announcement.
- Data Source Support: Multi-dataset analytics currently supports Snowflake and relational databases, with semantic catalog integration for AWS Glue, Databricks Unity Catalog, and Collibra.
- Application Integrations: Quick connects to Slack, Microsoft Teams, Microsoft Outlook, CRMs, and local desktop files, with the desktop client running natively without a browser.
- Regional Availability: Specific AWS region availability was not detailed in the announcement; prospective enterprise customers should consult AWS sales or the Quick product page for regional deployment details.
- No-Code Requirement: Agent creation and multi-dataset querying require no coding or SQL knowledge, making the features accessible to non-technical end users.
